Report NEP-CMP-2019-09-02

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Mossad, Omar S. & ElNainay, Mustafa & Torki, Marwan, 2019. "Modulations Recognition using Deep Neural Network in Wireless Communications," 2nd Europe – Middle East – North African Regional ITS Conference, Aswan 2019: Leveraging Technologies For Growth 201750, International Telecommunications Society (ITS).
• Jang, Youngsoo & Lee, Soyoung, 2019. "A Generalized Endogenous Grid Method for Models with the Option to Default," MPRA Paper 95721, University Library of Munich, Germany.
• Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
• Michel Alexandre & Gilberto Tadeu Lima, 2019. "Macroeconomic Impacts of Trade Credit: An Agent-Based Modeling Exploration," Working Papers, Department of Economics 2019_31, University of São Paulo (FEA-USP).
• Iordanis Kerenidis & Anupam Prakash & D'aniel Szil'agyi, 2019. "Quantum Algorithms for Portfolio Optimization," Papers 1908.08040, arXiv.org.
• Roos Elizabeth & Adams Philip, 2019. "Fiscal Reform – Aid or Hindrance: A Computable General Equilibrium (CGE) Analysis for Saudi Arabia," Working Papers 1317, Economic Research Forum, revised 21 Aug 2019.
• Manel Hamdi & Walid Chkili, 2019. "An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?," Working Papers 13, Economic Research Forum, revised 21 Aug 2019.
• David Byrd & Tucker Hybinette Balch, 2019. "Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency," Papers 1908.08168, arXiv.org.
• Songul Tolan, 2018. "Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges," JRC Working Papers on Digital Economy 2018-10, Joint Research Centre.
• Lotfi Boudabsa & Damir Filipović, 2019. "Machine Learning With Kernels for Portfolio Valuation and Risk Management," Swiss Finance Institute Research Paper Series 19-34, Swiss Finance Institute.
• Christian Bayer & Blanka Horvath & Aitor Muguruza & Benjamin Stemper & Mehdi Tomas, 2019. "On deep calibration of (rough) stochastic volatility models," Papers 1908.08806, arXiv.org.
• Nicola Cufaro Petroni & Piergiacomo Sabino, 2019. "Fast Pricing of Energy Derivatives with Mean-reverting Jump-diffusion Processes," Papers 1908.03137, arXiv.org, revised Mar 2020.
• Jingyuan Wang & Yang Zhang & Ke Tang & Junjie Wu & Zhang Xiong, 2019. "AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks," Papers 1908.02646, arXiv.org.
• Albanesi, Stefania & Vamossy, Domonkos, 2019. "Predicting Consumer Default: A Deep Learning Approach," CEPR Discussion Papers 13914, C.E.P.R. Discussion Papers.
• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.